code: def easy_objective(config):
      # Hyperparameters
      width, height = config["width"], config["height"]
  
      for step in range(config["steps"]):
          # Iterative training function - can be any arbitrary training procedure
          intermediate_score = evaluation_fn(step, width, height)
          # Feed the score back back to Tune.
          train.report(
              {"iterations": step, "mean_loss": intermediate_score}
          )
  
file_path: ray/python/ray/tune/examples/logging_example.py
imports: import argparse
  import time
  from ray import train, tune
  from ray.tune.logger import LoggerCallback
label_desc: Use image node_id 3 for calling a global function with example usage: easy_objective(config) without return types